Senior Specialist Solutions Architect (AI/ML)

The shape of it

In the posting’s own words

As a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers in architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader.

What it asks for · 12

• Experience: 10+ years of hands-on industry DS/ML experience, with a focus on either:
• ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance.
• Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning, and deployment tools (e.g., HuggingFace, Langchain).
• Hands-on experience working with Distributed Spark based systems
• Experience with data engineering concepts or a good understanding of data engineering concepts
• Pre-sales or post-sales experience working with external clients across a variety of industry markets. Minimum of 5+ years of customer-facing experience would be preferred
• [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets
• Communication: Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences.
• Core Traits: Passion for lifelong learning, collaboration, and driving business value through AI.
• Education: Graduate degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research, etc) or equivalent practical experience.
• Can meet expectations for technical training and role-specific outcomes within 3 months of hire
• Can travel up to 30% when needed

Degree language

• Education: Graduate degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research, etc) or equivalent practical experience.

Tools and skills named

Words the posting leans on

• experience8×
• technical8×
• data6×
• engineering6×
• solutions5×
• customer4×
• genai4×
• industry3×
• platform3×
• advanced2×
• agentic systems2×
• applications2×
• architecting2×
• business2×
• complex2×
• data engineering2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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